AWS Lambda Features

AWS Lambda automatically scales to match the rate of incoming requests and scales down to zero during idle periods, requiring no manual configuration. Each Lambda function can scale up to 1,000 concurrent executions every 10 seconds incrementally, until reaching the account's concurrency limit.

AWS Lambda natively integrates with over 220 AWS services and 50 SaaS applications, enabling faster and easier application composition and innovation without the need to write custom code.

AWS Lambda runs on highly available AWS infrastructure, with AWS managing fault tolerance across multiple Availability Zones and Regions.

AWS Lambda natively supports Java, Go, PowerShell, Node.js, C#, Python, and Ruby code, as well as custom runtimes, allowing you to use your preferred runtime or any programming language without learning new tools or frameworks. You can package your code as ZIP files or container images, and deploy through multiple methods including the AWS Console, Infrastructure as Code (IaC), or CI/CD pipelines.

AWS Lambda integrates with a comprehensive set of security, observability, and compliance services, enabling alerts or automatic remediation of security threats. AWS Lambda provides built-in monitoring capabilities by automatically capturing and sending logs, metrics, and traces to AWS monitoring and observability services such as Amazon CloudWatch and AWS X-Ray. With Application Signals, AWS Lambda offers an out-of-the-box application performance monitoring (APM) tool to track throughput, availability, latency, faults, and errors in your serverless applications. Additionally, AWS Lambda supports seamless integration with third-party monitoring tools through Lambda extensions, making it easy to use your preferred tools for monitoring and troubleshooting your serverless applications.

AWS Lambda provides comprehensive tools and features to enhance the local development experience. You can seamlessly bring your code from the console to your local environment using the “Open in Visual Studio Code" feature. You can use dedicated toolkits for popular IDEs (such as VS Code) to author, build, debug, test, and deploy Lambda functions directly from your IDE. AWS Lambda also supports remote debugging and local testing of cloud functions, enabling rapid application iteration to changing business needs from your local environment.

AWS Lambda enables you to write less code and build applications faster through AI-assisted tools and capabilities. The Model Context Protocol (MCP) Server for AWS Lambda enables generative AI models to access and run Lambda functions as tools, allowing secure interaction with private resources and AWS services without code changes. Amazon Q CLI improves the local development experience by offering AI-assisted deployment and development capabilities. Additionally, tools like Kiro further augment the Lambda development workflow with AI capabilities.

AWS Lambda executes functions using Micro Virtual Machines (MicroVM) created by Firecracker on the AWS Nitro System, providing dedicated compute resources that are never shared between functions, customers, or AWS accounts. These execution environments operate within network-isolated Amazon VPCs managed by Lambda, where network ingress is strictly limited to Lambda-owned services and accounts. This comprehensive built-in isolation creates secure boundaries and minimizes potential security vulnerabilities and unauthorized access.

AWS Lambda undergoes regular third-party audits and is certified under a wide range of compliance programs, including SOC, HIPAA, PCI, and ISO. For the latest in Lambda certification and compliance readiness, please see the full services in scope.

AWS Lambda offers provisioned concurrency to keep Lambda functions initialized and hyper-ready to ensure consistent start-up performance with minimal cold start latency.

AWS Lambda SnapStart delivers faster startup performance by up to 10x for Java, and from several seconds to as low as sub-second for Python and .NET, with minimal or no changes to your function code.

Provisioned Mode for Lambda Event Source Mappings (ESM) allows you to configure throughput for  event source connectors, optimizing the performance of Apache Kafka event sources, including Amazon MSK and self-managed Kafka.

AWS Lambda offers flexibility in choosing between x86 and Arm-based processor architectures to  optimize both performance and cost. You can easily switch between architectures without code changes, allowing you to choose the most cost-efficient option for your specific workload requirements.